Evaporation of sulfuric acid from particles can be
important in the atmospheres of Earth and Venus. However, the equilibrium
constant for the dissociation of H
Suspended particulate matter in the atmosphere plays a key role in Earth's climate. Atmospheric aerosol particles affect the amount of solar radiation absorbed by the Earth system. This is accomplished either when atmospheric aerosol particles directly absorb or scatter incoming solar energy (causing warming or cooling) or when particles act as cloud condensation or ice nuclei (leading to an increase in cloud albedo, which causes cooling). A substantial fraction of particle number and mass across a wide range of environmental conditions arises from sulfur emissions (Clarke et al., 1998; Turco et al., 1982).
Sulfur in Earth's atmosphere in turn originates from natural phenomena like
volcanic eruptions and biota decomposition. Violent volcanic eruptions can
loft sulfur dioxide (SO
The atmospheric sulfate burden is substantially perturbed by sulfur
emissions associated with anthropogenic activities. The largest
anthropogenic source of sulfur is fossil-fuel combustion; coal is the
predominant source, but also heavy fuel oil is important (Öm et al.,
1996; Smith et al., 2001). Fossil-fuel combustion constitutes
Sulfur is also a crucial constituent in Venus' atmosphere, an environment
with very low relative humidity (RH) (Moroz et al., 1979; Hoffman et al.,
1980), forming the main cloud layer in the form of sulfuric acid droplets
(Donahue et al., 1982), which are maintained in an intricate photochemical
cycle (photooxidation of OCS; Prinn, 1973). Sulfuric acid's reaction paths
remain a subject of investigation (Zhang et al., 2010), which makes the
study of the sulfur cycle (including the sulfur species SO, SO
H
The sulfuric acid vapour pressure appears through the free-energy term in
the exponent of the new-particle formation rate (Volmer and Weber, 1926;
Stauffer, 1976). Quantitative theoretical predictions of nucleation rates
are highly uncertain because the pure H
While H
Furthermore, molecular H
H
For dilute aqueous solutions, Reaction (R1) is considered to be complete. However, when
the mole fraction of S(VI) exceeds
Even in the cleanest environments, such as the stratosphere, NH
In the CLOUD (Cosmics Leaving OUtdoor Droplets; Kirkby et al., 2011)
chamber at CERN, we measured the H
Details of the CLOUD chamber, the main element of the experimental setup
can be found in Kirkby et al. (2011) and Duplissy et al. (2016). For the
experiments described here, we formed and grew sulfuric acid particles in
the chamber by oxidising SO
We utilised the following instruments to measure gas-phase concentrations: a
SO
We measured the evolution of the aerosol number size distribution with a
scanning mobility particle sizer (SMPS; Wang and Flagan, 1990), which
recorded the dry particle mobility diameter in the size range from about 10
to 220 nm. We operated the SMPS system with a recirculating dried sheath
flow (RH
We measured aerosol particle chemical composition with an Aerodyne aerosol
mass spectrometer (AMS) quantifying sulfate, nitrate, ammonium and organics
for particles between 50 and 1000 nm aerodynamic diameter (Jimenez et al.,
2003; Drewnick et al., 2006; Canagaratna et al., 2007). The AMS provided
the mass concentration measurements (
To study aerosol particle evaporation, the formation of sulfuric acid
particles preceded. At the lowest H
Summary of the experimental conditions: temperature (
After the end of the particle formation period and during the initial steps
of evaporation, before the RH started to decrease, the aerosol size
distribution remained nearly constant. Subsequently, the RH decreased
gradually initiating the particle evaporation. When the RH reached a certain
low value (RH
Similarly, the AMS recorded the evaporation of particles (see Supplement,
Fig. S1). The AMS measurements showed that the particles were composed
almost exclusively of sulfuric acid (but not pure H
In the present work we use ADCHAM (Roldin et al., 2014, 2015) to study the
evolution of the particle number size distribution and particle chemical
composition. Instead of simulating the new-particle formation in the CLOUD
chamber, we use the measured particle number size distribution before the
UV lights are turned off as well as time sequences of RH,
Schematic of the ADCHAM model optimised for the sulfur particle evaporation at low RH.
Within an aqueous electrolyte solution, such as the
H
For relatively dilute H
Since AIOMFAC does not consider inorganic non-electrolyte compounds like
H
The reference state of the molecular species in eNRTL is defined as the pure
liquid. eNRTL provides mole-fraction-based activity coefficients for
H
If ammonium cation (NH
The thermodynamic model uses an iterative approach to calculate the particle
equilibrium mole fractions of H
Based on the particle diameters from the previous time step (which depend on
the particle water content), the thermodynamic model starts by calculating
In the gas phase only a fraction of H
In the gas phase, SO
We use Eqs. (11) and (12) to calculate the temperature-dependent sub-cooled
pure-liquid saturation vapour pressures for H
We calculate the saturation vapour pressures of H
As an alternative approach we also model the evaporation of H
We calculate the surface tension and density of the particles comprising a
ternary mixture of water, sulfuric acid and ammonium with parameterisations
given by Hyvärinen et al. (2005) that combine surface tension
parameterisations for (NH
We model the gas-particle partitioning (evaporation) of H
Equation (16) describes the contribution of species
Based on measurements of H
The electric field strength of the stainless-steel CLOUD chamber, in
contrast to smog chambers made of Teflon, is very low. Therefore, we can
neglect electrostatic deposition enhancements (for details on how ADCHAM
treats particle wall deposition losses see Roldin et al., 2014). We simulate
the particle-size-dependent deposition losses with the model from Lai and
Nazaroff (2000). The particle deposition loss depends on the friction
velocity (
We use ADCHAM to constrain the values of the thermodynamic equilibrium
coefficients,
In the model we address this by assuming either that the particles (prior to
evaporation) contained a small fraction of non-volatile organic
material (e.g. secondary organic aerosol, SOA) or that the particles
contained small amounts of ammonium, which prevented pure H
In order to fit the modelled particle number size distribution evolution to
the observations we performed several hundred simulations where we varied
Case 1: only H Case 2: a combination of H Case 3: practically only SO
Case 2 is further divided into two subcategories, Case 2a and 2b. In Case 2a
the H
Modelled particle-phase mole fractions of
Figure 2 shows an example of the modelled mole fractions of (a)
H
Particle shrinkage at low RH. Measured
In Fig. 3 we present the particle number size distribution evolution after
the shutter of the UV light is closed and the influx of water vapour to the
chamber is interrupted for experiment 2, performed at
Measured and modelled GMD evolution as a function of
Figure 4 compares the measured and modelled GMD evolution as a function of
(a) time and (b) RH for experiments 1 and 2 performed at a temperature of
With the Aspen Plus Databank pure-liquid saturation vapour pressure
parameterisations it is also possible to find similarly good agreement
between the modelled and observed GMD evolution during experiment 1 and 2
for cases 1, 2a, 2b and 3 (Fig. S8) with NH
The model simulations with non-volatile and non-water-soluble organics or
dimethylamine (DMA) as the particle-phase contaminant give nearly identical
results to those with NH
Instead of explicitly calculating the H
Based on data from Giauque et al. (1960), Eq. (15) and the pure-liquid
saturation vapour pressure parameterisation, Eq. (11) (N–K–L parameterisation), the modelled GMD
shrinkage is consistent with the observations for experiments 1 and 2 when
we consider the Case 1 (H
In an attempt to constrain how
For other acids like HNO
Measured and modelled GMD evolution as a function of
Figure 5 compares the measured and modelled GMD evolution during experiment 3.
For the simulations we use either the same temperature dependence as
suggested by Que et al. (2011) (
For the Case 1 simulation (see Supplement, Table S1, simulation 28) we use
Eq. (15) and the tabulated H
If we instead use the pure-liquid saturation vapour pressure
parameterisations from the Aspen Plus Databank (which have somewhat weaker
temperature dependences than Eqs. 11 and 12), the model results captures the
observed GMD evolution if both
For Case 2b and 3 simulations in which we assume that SO
Based on the simulations of experiment 3 we conclude that most of the S(VI)
that evaporated from the particles probably was in the form of
H
In the following section, we define an effective saturation concentration of
H
Modelled effective H
The observed atmospheric daytime range of the [H
These model results demonstrate that sulfuric acid can evaporate from
particles or be unable to contribute to their growth for atmospherically
relevant conditions, characterised by low relative humility, relatively high
temperatures and weak sources of NH
This study demonstrates, both experimentally and theoretically, the
importance of H The dissociation of H The equilibrium rate coefficient for the first dissociation stage of
H The equilibrium coefficient for the dehydration of H
The main factors limiting our estimation of
In order to be able to make an accurate prediction of the sulfate particles'
influence on global climate, their thermodynamic properties need to be
properly described in global climate models. Thus, our constraints on the
dissociation,
Our results are especially meaningful for high-altitude new-particle
formation (e.g. in the upper troposphere and stratosphere). It has been
previously reported that the particle formation (Brock et al., 1995) and the ion-induced nucleation (Lee et al., 2003; English et al., 2011) are sources of
new particles in high altitudes. In the upper troposphere and stratosphere
general circulation models coupled with aerosol dynamics models use aerosol
evaporation as a source of [H
In a changing climate it will become even more important to understand the
thermodynamic properties of the sulfur aerosol particles involved in the
development of polar stratospheric clouds and how sulfate aerosols
influence the stratospheric O
Requests for underlying material should be addressed to the corresponding author, Georgios Tsagkogeorgas (george.tsagkogeorgas@tropos.de).
GT and JD designed and performed the experiments. GT, JD and PR analysed the data. PR developed the model code. PR and GT performed the simulations. GT, JD, LR, JT, JGS, and AK collected the data and contributed to the analysis. GT, PR, JD, and NMD assisted in drafting the manuscript. GT, PR, JD, MB, JC, RCF, MK, NMD and FS contributed to scientific interpretation and editing of the manuscript. All authors contributed to the development of the CLOUD facility and analysis instruments and commented on the manuscript.
The authors declare that they have no conflict of interest.
We would like to thank CERN for supporting CLOUD with important technical and financial resources, and for providing a particle beam from the CERN Proton Synchrotron. We also thankPatrick Carrie, Louis-Philippe De Menezes, Jonathan Dumollard, Roberto Guida, Katja Ivanova, Francisco Josa, llia Krasin, Robert Kristic, Abdelmajid Laassiri, Osman Maksumov, Serge Mathot, Benjamin Marichy, Herve Martinati, Antti Onnela, Robert Sitals, Hansueli Walther, Albin Wasem and Mats Wilhelmsson for their important contributions to the experiment. This research has received funding from the EC Seventh Framework Programme (Marie Curie Initial Training Network “CLOUD-ITN” no. 215072 and “CLOUD-TRAIN” no. 316662, ERC-Starting “MOCAPAF” grant no. 57360 and ERC-Advanced “ATMNUCLE” grant no. 227463), the German Federal Ministry of Education and Research (project nos. 01LK0902A and 01LK1222A), the Swiss National Science Foundation (project nos. 200020 135307 and 206620 141278), the Academy of Finland (Centre of Excellence project no. 1118615 and other projects: 135054, 133872, 251427, 139656, 139995, 137749, 141217, 141451), the Finnish Funding Agency for Technology and Innovation, the Vaisala Foundation, the Nessling Foundation, the Austrian Science Fund (FWF; project no. J3198-N21), the Portuguese Foundation for Science and Technology (project no. CERN/FP/116387/2010), the Swedish Research Council, Vetenskapsradet (grant 2011-5120), the Presidium of the Russian Academy of Sciences and Russian Foundation for Basic Research (grants 08-02-91006-CERN and 12-02-91522-CERN), the US National Science Foundation (grants AGS1136479, AGS1447056, AGC1439551 and CHE1012293), the PEGASOS project funded by the European Commission under the Seventh Framework Programme (FP7-ENV-2010-265148), and the Davidow Foundation. We thank the tofTools team for providing tools for mass spectrometry analysis.
Pontus Roldin would like to thank the Cryosphere-Atmosphere Interactions in a Changing Arctic Climate (CRAICC) Nordic Top-Level Research Initiative and the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning FORMAS (project no. 214-2014-1445) for financial support.Edited by: Yafang Cheng Reviewed by: two anonymous referees